class_docstr: Dataset to manage the data loading, augmentation and generation. 
docstr: Get the data sample and labels with the index. 
docstr_tok: ["Get","the","data","sample","and","labels","with","the","index","."]
code: def __getitem__(self, index):
      """Get the data sample and labels with the index."""
      self.line = self.lines[index].strip().split()
      # load image
      if self.data_root:
          self.img = cv2.imread(
              os.path.join(self.data_root, self.line[0])
          )
      else:
          self.img = cv2.imread(self.line[0])
      # resize
      self.img = cv2.resize(self.img, (self.img_size, self.img_size))
      # obtain gt labels
      self.land = np.asarray(
          self.line[1 : (106 * 2 + 1)], dtype=np.float32
      )
      self.angle = np.asarray(
          self.line[(106 * 2 + 1) :], dtype=np.float32
      )
  
      # augmentation
      if self.transforms:
          self.img = self.transforms(self.img)
  
      return self.img, self.land, self.angle
  
file_path: nni/examples/nas/legacy/oneshot/pfld/datasets.py
imports: from __future__ import absolute_import, division, print_function
  import cv2
  import os
  import numpy
  from torch.utils import data
label_desc: Use image node_id 2 for calling the PFLDDatasets obj's underlying member method code with example usage: obj.__getitem__(index) and returns: self,  self,  self